DataStage Advanced Training

This course comprises Stage 2 within SmallNet’s Technical Training Track.

 

Objective:

Developing a more in-depth understanding of DataStage architectural design and techniques for solving complex issues.

The course is designed for prospective technical leads and architects. Participants have generally already attended the basic course and have some subsequent experience of using the tool (we recommend one month at least, preferably six months).

 

Course: DataStage Advanced Course 

This course is designed for DataStage developers who have achieved a basic level of skill with the product. It furthers knowledge of DataStage by discussing the underlying parallel job framework and by introducing more complex DataStage parallel job designs.

Topics include: the parallel architecture, compilation and execution, partitioning and collecting, sorting, buffering, parallel data types, database usage, stage and job design practices, and performance.

 

Skills Attained: lead DataStage developers will be able to:

  • Understand the framework development and runtime architecture.
  • Understand metadata in the framework.
  • Create jobs using advanced design techniques.
  • Design jobs using techniques for good performance and resource usage.
  • Extend the functionality of DataStage with build stages, wrapped stages, and external functions.
  • Choose the appropriate partitioning and collection algorithms to satisfy business,performance, and resource usage requirements.
  • Understand the difference between database stages.
  • Read the score to determine what is happening at runtime.
  • Understand configuration files.
  • Understand how buffering works in parallel jobs.